蛋白抗原微阵列在早期癌症中的抗体谱分析。

Expert opinion on medical diagnostics Pub Date : 2012-05-01 Epub Date: 2012-03-22 DOI:10.1517/17530059.2012.672969
Brian C-S Liu, Daniel A Dijohnson, Dennis J O'Rourke
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引用次数: 8

摘要

正常细胞中不存在的蛋白质,即癌细胞,可能引起宿主免疫反应,导致抗体的产生,抗体可能与这些肿瘤相关蛋白质发生反应。近年来,越来越多的报告表明,自身抗体谱分析可能为癌症的检测提供了一种替代方法。然而,大多数抗原-自身抗体反应性的研究都依赖于重组蛋白。重组蛋白缺乏天然蛋白应有的翻译后修饰。由于这一限制,天然或天然蛋白抗原微阵列在分析抗体反应方面越来越受欢迎。涵盖领域:i)举例说明自身抗体作为早期癌症标志的一些例子;Ii)简要概述各种蛋白质抗原微阵列平台;Iii)说明天然或天然蛋白质微阵列在发现潜在生物标志物中的使用,iv)讨论天然蛋白质抗原微阵列相对于其他方法的优势。专家意见:蛋白质微阵列平台的性质有利于多路复用,这扩大了发现许多重大疾病的有效生物标志物的潜力。然而,主要的挑战将是将微阵列平台集成到多路临床诊断工具中,因为主要的缺点是阵列之间结果的可重复性和变异系数,以及阵列平台到更自动化平台的可移植性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Antibody profiling with protein antigen microarrays in early stage cancer.

Introduction: Proteins not present in normal cells, that is, cancer cells, may elicit a host immune response that leads to the generation of antibodies that might react with these tumor-associated proteins. In recent years, a growing number of reports have showed that autoantibody profiling may provide an alternative approach for the detection of cancer. However, most studies of antigen-autoantibody reactivity have relied on recombinant proteins. Recombinant proteins lack the proper post-translational modifications present in native proteins. Because of this limitation, native or natural protein antigen microarrays are gaining popularity for profiling antibody responses.

Areas covered: i) To illustrate some examples of autoantibodies as signatures for early stage cancer; ii) to briefly outline the various protein antigen microarray platforms; iii) to illustrate the use of native or natural protein microarrays in the discovery of potential biomarkers and iv) to discuss the advantages of native protein antigen microarrays over other approaches.

Expert opinion: The nature of protein microarray platforms is conducive to multiplexing, which amplifies the potential for uncovering effective biomarkers for many significant diseases. However, the major challenge will be in integrating microarray platforms into multiplexed clinical diagnostic tools, as the main drawback is the reproducibility and coefficient of variation of the results from array to array, and the transportability of the array platform to a more automatable platform.

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